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Professional services giant Marsh McLennan recently pulled back the curtains on LenAI, a generative AI tool the firm has developed to make its 85,000-plus employees more productive .

LenAI is based on large language models from OpenAI. Notably, Marsh McLennan says that it’s hosting those models internally, which means any data employees feed into the software won’t leave the four walls of the organization.

Marsh McLennan describes LenAI as a general-purpose productivity tool. The software, the firm says, can help employees pull information from the web, quickly scan documents for useful bits of knowledge and perform business calculations.

Marsh McLennan has equipped LenAI with a number of governance safeguards. According to the firm, the tool was built to retain as little data as necessary to support employees’ work. Moreover, employees who use the tool are given special AI training to ensure they use the technology responsibility.

Marsh McLennan says LenAI is already used by several internal teams, including the private equity group at its Oliver Wyman management consulting business. The group assistants private equity firms with tasks such as due diligence, or the process of checking if a company a fund is about buy has its books in order. 

“We’re using it in our private capital teams to industrialize a lot of the way in which we do kind of due digital intelligence work for private equity firms,” explained Vivek Sen, the head of Oliver Wyman’s IT consulting division. “So much of what our case teams do relies on rapid ingestion of a lot of data, client data, internal data, first drafts.”

Marsh McLennan says that LenAI is helping some employees save eight hours per week. The tool is also valuable for another reason: it will give the firm an opportunity to gain more experience with large-scale AI rollouts.

Through its Olivier Wyman consulting business, Marsh McLennan assists corporations with machine learning projects. The insights Marsh McLennan will gain from rolling out a custom AI assistant to its 85,000 employees will prove handy when it works with corporate clients on large-scale machine learning initiatives. 

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